A lot of public organisms, from governments to global funds are investing into more and better reproductive health care services in low income countries. This means measuring availability, quality but also accessibility of key services for the target populations. In particular, taking into account the population distribution and the travel time health systems users need to reach the nearest health center is key to identify challenges to access these services.

We'll show how we got from a single question "How many women between 15 and 35 years old live more than one hour from maternal care" to getting and answer by combining availability, quality and geographical accessibility. We now further this work by building a routine computation platform to offer the most updated data to decision makers at any time.

We'll share how the modeling and computing strategy evolves in low-availability and low-quality data environments.